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Malaria Detection with Deep CNNs by GEORGE is a document available to read on EtoBox.

What is Malaria Detection with Deep CNNs about?

The document summarizes research on using a deep convolutional neural network (CNN) to detect malaria from digitized microscopic images of red blood cells. Key points: 1) A CNN was trained on a dataset of 32,353 segmented red blood cell images from malaria-infected patients to classify cells as infected or uninfected. 2) Various preprocessing techniques were applied to the images including min-max normalization and data augmentation to improve the CNN

Author

GEORGE

Language

EN